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Advanced Computer Vision (at SEAS)
SCI 6275

Jointly Offered with: Faculty of Arts & Sciences as COMPSCI 2831

Course Information

Description

Vision as an ill-posed inverse problem: image formation, two-dimensional signal processing; feature analysis; image segmentation; color, texture, and shading; multiple-view geometry; object and scene recognition; and applications.

Required Preparation.  CS 2831 assumes students have had significant programming experience with Python and NumPy, ideally with some exposure to PyTorch or JAX. Experience with Matlab or Julia can be a viable substitute for students who are self-motivated to pick up Python on the fly. CS 2831 also assumes students have taken an undergraduate course in computer vision (e.g., ES 1431), or that they have taken a course in each of the following: probability (e.g. ES 150 or Stat 110),  linear algebra (e.g., AM 22a or Math 21b), and signal processing (e.g., ES 156 or AM 104).

Class Notes

This course is offered by SEAS and jointly offered with the GSD. Please refer to the FAS academic calendar for start of term information and to the CS 1710 SEAS listing for classroom information. 

School Graduate School of Design
Credits 4
Cross Reg

Not Available for Cross Registration

Department Architecture
Course Component Lecture
Instruction Mode In Person
Grading Basis GSD Graded